Dynamic Multi Granularity Service Composition

Authors

  • A. Ravi  Department of CSE, JNTUACE, Anatapur, Andhra Pradesh, India
  • Dr. B. Lalitha  Assistant Professor, Department of CSE, JNTUACE, Anatapur, Andhra Pradesh, India

Keywords:

Service Selection, Service Composition , Cloud Computing

Abstract

The trend is for enterprises to outsource parts of their services, in order to concentrate on their own core `businesses. Meanwhile, users usually need to compose multiple different services to create a sophisticated application. Through the service-oriented architecture paradigm, users can compose elementary services to form new value added services through the process of service composition. In template-based service composition, an abstract composite service, consisting of a collection of abstract services orchestrated by workflow patterns, is first defined and then instantiated and executed at run time by binding abstract services to concrete ones. This dynamic binding ensures a loose -coupling of services and all so-called QoS-aware service composition problem. In existing work, to expand the selection scope using the concept of generalized component services, a backtracking-based algorithm and an extended genetic algorithm(GA) has been applied for finding an optimized solution and near-optimal solution respectively in composition service The proposed work, will adopt the multi-granularity service composition automatically at run time. This will be useful to study how to extend other Meta-heuristic algorithms along with Tabu-search algorithm used for efficient optimization service selection.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2017-08-31

Issue

Volume 2, Issue 4, July-August-2017

Section

Research Articles

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How to Cite

[1]
A. Ravi, Dr. B. Lalitha, " Dynamic Multi Granularity Service Composition, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 4, pp.584-590, July-August-2017.